Kinematics Model Optimization Algorithm for Six Degrees of Freedom Parallel Platform

The attitude closed-loop control of the parallel platform in the working space needs to determine the relationship between the pose of the top moving platform and the length of each mechanical arm, that is, the kinematics problem of the parallel platform. In this study, the kinematics model of the s...

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Vydané v:Applied sciences Ročník 13; číslo 5; s. 3082
Hlavní autori: Liu, Mingzhe, Gu, Qiuxiang, Yang, Bo, Yin, Zhengtong, Liu, Shan, Yin, Lirong, Zheng, Wenfeng
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Basel MDPI AG 01.03.2023
Predmet:
Accuracy
Algorithms
Control systems
Independent sample
Kinematics
Mathematical optimization
multivariate polynomial regression
Newton iterative
parallel platform
ISSN:2076-3417, 2076-3417
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Shrnutí:The attitude closed-loop control of the parallel platform in the working space needs to determine the relationship between the pose of the top moving platform and the length of each mechanical arm, that is, the kinematics problem of the parallel platform. In this study, the kinematics model of the six-degree-of-freedom parallel platform was established. The kinematics forward solution algorithm based on Newton–Raphson iteration was studied. The kinematics forward solution method usually adopts a numerical solution, which often needs multiple iterations, and the algorithm has a poor real-time performance. In order to improve the real-time performance of the parallel platform control system, a multivariate polynomial regression kinematics forward solution algorithm is proposed in this paper. Moreover, by combining the multivariate polynomial regression with the Newton iterative method, we obtained an efficient solution algorithm with controllable solution accuracy. The effectiveness of the proposed method was verified by simulation tests and physical tests.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2076-3417
2076-3417
DOI:10.3390/app13053082